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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/10054/10557

Title: ARTIFICIAL NEURAL NETWORKS FOR THE PREDICTION OF MECHANICAL-BEHAVIOR OF METAL-MATRIX COMPOSITES
Authors: MUKHERJEE, A
SCHMAUDER, S
RUHLE, M
Issue Date: 1995
Publisher: PERGAMON-ELSEVIER SCIENCE LTD
Citation: ACTA METALLURGICA ET MATERIALIA, 43(11), 4083-4091
Abstract: In this paper we demonstrate the power of artificial neural networks in predicting strengthening in the transverse direction of metal matrix composites by regularly arranged strong fibers. A neural network is trained in different ways based on a numerical study in which the fiber volume fraction and the matrix hardening ability was studied systematically for fibers in a hexagonal arrangement loaded at 0 and 30 degrees transverse direction and for a square arrangement of fibers loaded at 0 and 45 degrees transverse directions. Strengthening predictions are then made for hardening cases of both fiber arrangements which were not covered by the finite element calculations as well as for arbitrary loading directions not achievable by simple finite element unit cell calculations in the case of square fiber arrangements.
URI: http://dx.doi.org/10.1016/0956-7151(95)00076-8
http://dspace.library.iitb.ac.in/xmlui/handle/10054/10557
http://hdl.handle.net/10054/10557
ISSN: 0956-7151
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